Avoid unexpected conversion with PyArrayLike1

Author: mattiapenati

src/array_like.rs

@@ -42,6 +42,25 @@ impl Coerce for AllowTypeChange {
     const VAL: bool = true;
 }
 
+trait IsNumpyNDArray {
+    fn is_numpy_ndarray(&self) -> PyResult<bool>;
+}
+
+impl<'py> IsNumpyNDArray for Borrowed<'_, 'py, PyAny> {
+    fn is_numpy_ndarray(&self) -> PyResult<bool> {
+        let py = self.py();
+
+        static NDARRAY: PyOnceLock<Py<PyAny>> = PyOnceLock::new();
+        let ndarray = NDARRAY
+            .get_or_try_init(py, || {
+                get_array_module(py)?.getattr("ndarray").map(Into::into)
+            })?
+            .bind(py);
+
+        self.is_instance(ndarray)
+    }
+}
+
 /// Receiver for arrays or array-like types.
 ///
 /// When building API using NumPy in Python, it is common for functions to additionally accept any array-like type such as `list[float]` as arguments.
@@ -151,7 +170,9 @@ where
 
         let py = ob.py();
 
-        if matches!(D::NDIM, None | Some(1)) {
+        // If the input is already an ndarray and `TypeMustMatch` is used then any conversion
+        // should be performed.
+        if (C::VAL || !ob.is_numpy_ndarray()?) && matches!(D::NDIM, None | Some(1)) {
             if let Ok(vec) = ob.extract::<Vec<T>>() {
                 let array = Array1::from(vec)
                     .into_dimensionality()